Lab 2 completion map
The lab asks you to calculate, interpret and defend choices using your own generated case. Understanding the result matters more than copying output.
| Section | What you must demonstrate |
|---|---|
| 1 | Observational unit; response-rate versus observed-mean denominator; ordinal/category/ID meaning |
| 2 | Eight-number arithmetic, squared units, n versus n-1 and software defaults |
| 3 | Stated quartile convention; sensitivity to a changed maximum; impossible score versus valid high usage |
| 4 | Four plot descriptions; binning; why zero skewness does not prove normality |
| 5 | Fences versus observed whiskers; source checks; group summaries; same mean and SD but different needs |
| 6 | Observed proportions versus the normal-model rule, without treating approximation as proof |
| 7 | Reference-group z-scores; zero SD; percentile contrast; bottle specification |
| 8 | Typical-use versus total-workload recommendation with own case code, numbers and limitations |
The notebook uses your ID to generate its seed and case code. Keep the same ID and use your own results. The lecture's 1,200-student figures do not replace your 240-student lab results. Restart and run all before submission, and do not delete a high-use student merely because a fence flags them.
Sources: W2 PDF pp. 2-60; L2 Sections 1-8. The personalised Lab 2 has 240 synthetic students, unlike the 1,200-student lecture dataset. Do not mix their numbers.
The lecture's question-first approach decides which summary to use: a typical student and total observed workload are different requests.
Practice problems
Supplementary study questions on the lecture concepts — not verbatim exam questions. Each answer counts toward spaced review.
1. Conceptual understanding
Definitions and distinctions.
Which numbers belong in the personalised Lab 2 report?
What is good evidence that you have learned a lab calculation?
2. Application
Apply the concept to a case or calculation.
A student's lab has 240 rows while the lecture has 1,200. Which values belong in their case report?
Which answer shows understanding of an outlier flag?
3. Interpretation and limitations
Evaluate assumptions and justify conclusions.
Which pair fits typical use and total observed workload respectively?
Which is the strongest final lab check?
Explain it in writing
Self-checked, not marked. Write a few sentences, then compare with the example answer. Your writing is saved as you type.
Show an example answer
Restart and run all cells, use a consistent ID/case code, verify calculations and units, and explain the actual output rather than leaving only charts or numbers.
Check: did you answer the question, use evidence or working, and avoid claiming more than the evidence supports?
Show an example answer
It shows where the evidence ends. For example, observed platform use may miss offline work or missing responses, so the recommendation should not claim to measure all learning.
Check: did you answer the question, use evidence or working, and avoid claiming more than the evidence supports?